Nowadays, data mining has been playing an important role in the various disciplines of sciences and technologies. For computer security, data mining are introduced for helping intrusion detection System (IDS) to detect intruders correctly. However, one of the essential procedures of data mining is feature selection, which is the technique (commonly used in machine learning) for selecting a subs...

This thesis develops a spatio-temporal data mining method for uncertain water reservoir data. The goal of the data mining method is to learn from a history human reservoir operations in order to derive an automated controller for a reservoir system. Spatio-temporal data mining is a challenging task due to the reasons: (1) spatio-temporal datasets are usually much larger than spatial data sets, ...

Feature selection is one of the fundamental problems in pattern recognition and data mining. A popular and effective approach to feature selection is based on information theory, namely the mutual information of features and class variable. In this paper we compare eight different mutual information-based feature selection methods. Based on the analysis of the comparison results, we propose a n...

Evolutionary algorithms have been successfully used in different data mining problems. Given that the prototype selection problem could be seen as a combinatorial problem, evolutionary algorithms have been used to solve it with promising results. This chapter presents an evolutionary data mining application known as evolutionary prototype selection. Various approaches have been proposed in the ...

This work presents the principle of optimal model truck selection for waste transport at open pit Gacko. The analysis was performed three types trucks: Belaz 7555, 75491 and 75135. Selection done using AHP method from group multicriteria decisionmaking methods. results technological procedure Gacko evaluation most important criteria an type selection. In assessment degree their impact, a questi...

The purpose of this study is to demonstrate the benefit of using common data mining techniques on survey data where statistical analysis is routinely applied. The statistical survey is commonly used to collect quantitative information about an item in a population. Statistical analysis is usually carried out on survey data to test hypothesis. We report in this paper an application of data minin...

This paper proposes a method for creating a high quality collection of researchers’ homepages. The proposed method consists of three phases: rough filtering of the possible web pages, accurate evaluation of the web pages and precise selection of the correct homepages. For the rough filtering, the authors first define content-based keyword-lists, then generate filtering rules and relax the rules...

Feature selection is an important data preprocessing technique and has been widely studied in data mining, machine learning and granular computing. In this paper, we introduced an effective feature selection method using the hybrid approaches, that is, use the mutual information to select the candidate feature set, then, obtain the super-reduct space from the candidate feature set by a wrapper ...

This paper analysis and criticizes the way of using, functioning the intrusion detection system in data mining. Understanding the techniques. data mining approach such as intrusion detection system using association datasets where as in event correlation data mining method we will maintain. traffic analysis and anomaly intrusion detection systems are needed. log data by using a knowledge discov...

In direct marketing large amounts of customer data are collected that might have some complex, non linear relation to customer behavior. Data mining techniques can ooer insight in these relations. In this paper we give a basic introduction in the application of data mining to direct marketing. Best practices for data selection, algorithm selection and evaluation of results are described and ill...